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A Novel Deep-sea Image Enhancement Method
被引:1
|作者:
Li, Yujie
[1
]
Lu, Huimin
[1
]
Serikawa, Seiichi
[1
]
机构:
[1] Kyushu Inst Technol, Dept Elect Engn & Elect, Kitakyushu, Fukuoka 804, Japan
关键词:
Underwater imaging;
Image processing;
Mineral detection;
Energy;
Sustainability;
FILTER;
D O I:
10.1109/IS3C.2014.143
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
Remote robotic exploration holds vast potential for gaining knowledge about extreme environments, which is difficult accessed by humans. In the last two decades, various underwater devices were developed for detecting the mines and mine-like objects in the deep-sea environment. However, there are some problems in recent equipment, like poor accuracy of mineral objects detection, without real-time processing, and low resolution of underwater video frames. Consequently, the underwater objects recognition is a difficult task, because the physical properties of the medium, the captured video frames are distorted seriously by scattering, absorption and noise. In this paper, we are considering utilizing the image processing methods to determine the mineral location and to recognize the mineral actually within a little processing time. The experiments show that the average PSNR is improved by at least about 1.5dB than the state-of-the-art-methods, and SSIM is improved about 0.01.
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页码:529 / 532
页数:4
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